Improving the Operability of the Cosmic-ray Neutron Soil Moisture Method: Estimation of Soil Calibration Parameters Using Global Datasets

Abstract:

Despite its critical importance to global food security, approximately 60% of water used for agriculture is wasted each year through inadequate water conservation, losses in distribution, and inefficient irrigation. Therefore, in order to coordinate a strategy to accomplish the agricultural demands in the future we must maintain a stable global food and water trade while increasing crop yield and efficiency. This research aims to improve the operability of the novel cosmic-ray neutron method used for estimating field scale soil moisture. The sensor works by passively counting the above ground low-energy neutrons which correlates to the amount of water in the measurement volume (a circle with radius of ~300 m and vertical depth of ~30 cm). Because the sensor responds to different forms of water (sources of hydrogen), estimates of background water in the mineral soil and soil organic matter must be accounted in order to minimize measurement error. Here we compared field-scale estimates of soil mineral water and soil organic matter with readily available global datasets. Using the newly compiled 1 km resolution Global Soil Dataset (GSDE), we investigate the correlation between (1) soil mineral water and clay content and (2) in-situ soil organic material. Preliminary results of in-situ samples from forty study sites around the globe suggest the GSDE dataset has sufficiently low bias and uncertainty (~ within 0.01 g/g of water equivalent) to better isolate the soil moisture signal from the neutron count information. Incorporation of this dataset will allow for real-time soil moisture mapping of hundreds of center-pivots using the mobile cosmic-ray sensor without the need of time-consuming in-situ soil sampling. The incorporation of this novel technique for soil moisture management has the potential to increase the efficiency of irrigation water use.